Integration Of Various Data Research Articles

Artificial Intelligence in the Differential Diagnosis of Cardiomyopathy Phenotypes.

Artificial intelligence (AI) is rapidly being applied to the medical field, especially in the cardiovascular domain. AI approaches have demonstrated their applicability in the detection, diagnosis, and management of several cardiovascular diseases, enhancing disease stratification and typing. Cardiomyopathies are a leading cause of heart failure and life-threatening ventricular arrhythmias. Identifying the etiologies is fundamental for the management and diagnostic pathway of these heart muscle diseases, requiring the integration of various data, including personal and family history, clinical examination, electrocardiography, and laboratory investigations, as well as multimodality imaging, making the clinical diagnosis challenging. In this scenario, AI has demonstrated its capability to capture subtle connections from a multitude of multiparametric datasets, enabling the discovery of hidden relationships in data and handling more complex tasks than traditional methods. This review aims to present a comprehensive overview of the main concepts related to AI and its subset. Additionally, we review the existing literature on AI-based models in the differential diagnosis of cardiomyopathy phenotypes, and we finally examine the advantages and limitations of these AI approaches.

Просторово-динамічний моніторинг у забезпеченні управління енергетичною безпекою підприємств

The problems of ensuring the management of energy security of the enterprise of the electric power system in the context of dynamic changes are considered. The article proposes a methodical basis for managing the energy security of enterprise, which allows taking into account the strategic tasks of managing the energy security of enterprise, the goals of the energy security management system of enterprise and its basic principles. It is proved that one of the elements of ensuring the management of energy security of enterprise is the spatial and dynamic monitoring of external and internal negative factors in the form of threats and risks, both for the energy enterprise itself as a whole and for its objects of generation, transmission, distribution and consumption of energy. This is an effective method of monitoring and control within the framework of ensuring the management of the energy security of the enterprise and the normal functioning of various energy objects and processes. The main directions of research and analysis of energy security on the basis of spatial-dynamic monitoring are allocated. The essence and substantive sequence of formation of the stages of spatial-dynamic monitoring of energy security of enterprise as an economic process in the current conditions of development of the electric power system at the macro-, meso- and micro-levels of the economy are studied, and an algorithm for implementing the stages of its conduct is proposed. The article proposes the implementation of the functions of spatial-dynamic monitoring on the basis of the use of integrated automated management systems of the energy enterprise, which allow in real time to generate management decisions, the effectiveness of which should be adjusted to reduce the impact or complete elimination of threats to the energy security of the enterprise. The selected instruments provide the integration of various data and their in-depth analysis, which will allow enterprises to effectively manage energy security in conditions of uncertainty and change. The use of modern technologies and methods will allow adapting to market dynamics and increasing the resilience of energy systems.

Integrated geological data, 3D post‐stack seismic inversion, depositional modelling and geostatistical modelling towards a better prediction of reservoir property distribution for near‐field exploration: A case study from the eastern Sirt Basin, Libya

De‐risking the hydrocarbon potential in near‐field exploration is one of the most important procedures in the exploration of hydrocarbons, and it requires the integration of various data to predict the reservoir characteristics of the prospect area more accurately. In this work, wells and 3D seismic data from the Libyan producing oil fields were utilized to demonstrate how well this technique worked to improve and describe the hydrocarbon potential of the carbonate geobody that corresponds to the Palaeocene Upper Sabil Formation, which was revealed by new seismic data. This study integrates different types of data, including 3D seismic, seismic acoustic impedance, depositional history and geostatistical analysis, to predict the facies, reservoir porosity and permeability distributions and then visualize them in a 3D reservoir model. The 3D seismic data analysis revealed the presence of a clear seismic anomaly geobody (GB) that has never been penetrated by any well. The sedimentological analysis for the well adjacent to the GB indicated a deep‐water depositional environment as turbidites surrounded by deep‐water mud dominated facies. The Upper Palaeocene interval in the study area was subdivided based on the depositional facies and seismic stratigraphy into eight zones that were used to build the reservoir model framework. According to the porosity permeability relationships, the carbonate facies has been classified into five E‐Facies, that is, soft highly argillaceous limestone, hard argillaceous limestone, porous limestone (<20% porosity, and >30% shale volume), medium quality limestone (10–20% porosity, and >30% shale volume) and tight limestone (<10% porosity, and >30% shale volume). The rock physics and inversion feasibility analysis indicated that the acoustic impedance (AI) can be used to predict the porosity but not the lithology or the fluid content. The Bayesian classification has shown excellent results in predicting and modelling the reservoir facies distribution within the study area, utilizing the integration of gross depositional maps (GDEs), wells and seismic data. The reservoir quality of the GB was predicted by using the post‐stack seismic inversion, which indicated a high porosity interval (25%–30%). Moreover, the statistical analysis integrated with the well and seismic data was used to predict the GB permeability. The predicted permeability was reasonably high (40–60 mD). The final E‐facies show an excellent match with the input well data and an excellent match with the blind wells that were used for result quality control (QC) with higher vertical resolution. The developed model can be used as a guide for de‐risking the studied GB hydrocarbon potential in the studied basin, and it can be applied in other similar geological conditions worldwide for exploring underexplored reservoirs and de‐risking their hydrocarbon potential.

A research on data integration and application technology of urban comprehensive pipe gallery based on three‐dimensional geographic information system platform

AbstractThree‐dimensional Geographic Information System (3D GIS) technology is often used in geology, mining, hydrology and other fields. It is also used in intelligent management of urban comprehensive pipe gallery projects, because the real environment with the sky, ground, and underground can be intuitively simulated in the virtual reality environment by 3D GIS platform. Through the research on data integration and application technology of urban comprehensive pipe gallery, the 3D model of comprehensive pipe gallery project data can be created based on Building Information Modelling and GIS technologies, and a comprehensive underground pipelines network management information system has been developed to realise the integration of various data, including 3D data of comprehensive pipe gallery model and underground pipe network model, 2D or 3D GIS data of the ground and underground etc. On this basis, the functions of intelligent planning and approval management, the safety analysis and disaster prevention planning and decision‐making of urban comprehensive pipe gallery projects can be further realised. The research results have been applied to the planning and construction process management of the comprehensive pipe gallery project in the sub‐centre of Beijing.

Information concept of the human health phenomenon as a guarantee of bioecosystem stability

The current idea of the phenomenon of human health is strongly associated with a harmonious, well-developed personality. A healthy person in all respects can be called one who adequately responds and adapts to the changing conditions of the ecological, biological and social environment. The main prerequisites for health are the stability of the bioecosystem and sustainable resources. Aim/tasks is the theoretically substantiate the information-structural model of human health and the characteristics of its components. The theoretical and methodological basis of the work was the synergistic use of the principles of science and a systematic approach, which led to the choice of research methods: general scientific (analysis, synthesis, systematization, generalization of literary sources); interdisciplinary (structural-system approach, axiological method). Based on the use of the method of information-structural modeling, the modern trend of natural science is substantiated, which is the key to the stability of the bioecosystem - the information model of human health. It consists of the following blocks: information field of knowledge of the main subject areas; information and technological base of research; information and organizational management tools. The basics of a new interdisciplinary approach to the formation of a generalized idea of the phenomenon of human health from the standpoint of information-structural modeling: systematized information concept of integrated health as a unity of physical, mental and social health, verified it, obtained information about the system in as a whole by translating verbal-qualitative information into quantitative assessments. Conclusions. It is emphasized that the information space of individual health statuses is a holistic multidimensional dynamic system of a certain structure, in which the system-hierarchical homeostasis of interaction of physical, mental and social health statuses at different hierarchical levels is realized. It is proved that the information concept of the phenomenon of human health promotes the further integration of various data, builds constructive ways to formalize complex natural objects, and determines the stable functioning of the bioecosystem.

Trust in open data applications through transparency

Open data provide great potential for society, for example, in the field of smart cities, from which all citizens might profit. The trust of these citizens is important for the integration of various data, like sensitive user data, into an open data ecosystem. In the following study, we analyzed whether transparency about the application of open data promotes trust. Furthermore, we formulated guidelines on how to create transparency regarding open data in an ethical way. Using an open-data-based fictitious smart city app, we conducted an experiment analyzing to what extent communication of the technical open data application process and the ethical self-commitment for the transparent communication of data application affect trust in the app’s provider. The results indicate that the more information users obtain regarding the use of open data, the more trustworthy they perceive the app provider to be, and the more likely they are to use the app.

Hazardous waste landfill site selection in Western Ghana: An integration of multi-criteria decision analysis and geographic information system.

Most cities in developing countries are fast industrialising, leading to an increased hazardous waste generation. Though disposal occupies the bottom of the waste management hierarchy, it is an important component of the waste management chain, requiring greater focus to mitigate its environmental and human health effects. The selection of a hazardous waste landfill site is a complex decision-making process since it requires the consideration of several laws and regulations and the integration of various data. This study presents a multi-criteria decision analysis for selecting hazardous waste landfill sites in Western Ghana. Thirty-two evaluation criteria arranged according to four hierarchy levels were selected for the study. The selected criteria considered geo-environmental, economic and social factors. Twenty-one intermediate suitability maps were created, which were then aggregated to produce a composite landfill suitability map of the study area. To narrow down the search for space for landfill sites, optimality criteria were applied on the composite suitable map to select the best locations for landfill. The application of the optimality criteria led to the selection of 5% of the study area as optimal for landfill sites. However, the final decision for landfill site selection will require further in situ studies. Overall, this research provides a proven landfill site selection methodology, which provides essential support for decision-makers.

A Conceptual Approach to Complex Model Management with Generalized Modelling Patterns and Evolutionary Identification

Complex systems’ modeling and simulation are powerful ways to investigate a multitude of natural phenomena providing extended knowledge on their structure and behavior. However, enhanced modeling and simulation require integration of various data and knowledge sources, models of various kinds (data-driven models, numerical models, simulation models, etc.), and intelligent components in one composite solution. Growing complexity of such composite model leads to the need of specific approaches for management of such model. This need extends where the model itself becomes a complex system. One of the important aspects of complex model management is dealing with the uncertainty of various kinds (context, parametric, structural, and input/output) to control the model. In the situation where a system being modeled, or modeling requirements change over time, specific methods and tools are needed to make modeling and application procedures (metamodeling operations) in an automatic manner. To support automatic building and management of complex models we propose a general evolutionary computation approach which enables managing of complexity and uncertainty of various kinds. The approach is based on an evolutionary investigation of model phase space to identify the best model’s structure and parameters. Examples of different areas (healthcare, hydrometeorology, and social network analysis) were elaborated with the proposed approach and solutions.

Forest sector carbon analyses support land management planning and projects: assessing the influence of anthropogenic and natural factors

Management of forest carbon stocks on public lands is critical to maintaining or enhancing carbon dioxide removal from the atmosphere. Acknowledging this, an array of federal regulations and policies have emerged that requires US National Forests to report baseline carbon stocks and changes due to disturbance and management and assess how management activities and forest plans affect carbon stocks. To address these requirements with the best-available science, we compiled empirical and remotely sensed data covering the National Forests (one fifth of the area of US forest land) and analyzed this information using a carbon modeling framework. We demonstrate how integration of various data and models provides a comprehensive evaluation of key drivers of observed carbon trends, for individual National Forests. The models in this framework complement each other with different strengths: the Carbon Calculation Tool uses inventory data to report baseline carbon stocks; the Forest Carbon Management Framework integrates inventory data, disturbance histories, and growth and yield trajectories to report relative effects of disturbances on carbon stocks; and the Integrated Terrestrial Ecosystem Carbon Model incorporates disturbance, climate, and atmospheric data to determine their relative impacts on forest carbon accumulation and loss. We report results for several National Forests across the USA and compare their carbon dynamics. Results show that recent disturbances are causing some forests to transition from carbon sinks to sources, particularly in the West. Meanwhile, elevated atmospheric carbon dioxide and nitrogen deposition are consistently increasing carbon stocks, partially offsetting declines due to disturbances and aging. Climate variability introduces concomitant interannual variability in net carbon uptake or release. Targeting forest disturbance and post-disturbance regrowth is critical to management objectives that involve maintaining or enhancing future carbon sequestration.

A Multiagent Approach to Database Migration for Big Data Systems

Presented in this paper is a possible solution for speeding up the integration of various data in the big data mainstream. The data enrichment and convergence of all possible sources is still at the beginning. As a result, existing techniques must be retooled in order to increase the integration of already existing databases or of the ones specific to Internet of Things in order to use the advantages of the big data to fulfill the final goal of web of data creation. In this paper, semantic web-specific solutions are used to design a system based on intelligent agents. It tries to solve some problems specific to automation of the database migration system with the final goal of creating a common ontology over various data repositories or producers in order to integrate them into systems based on big data architecture.

A Framework and Implementation of an Online Research Management System

Objectives: The Implementation of Research Management System (RMS) is due to the existence of major drawbacks in the present system which includes manual process for carrying out various technical tasks. To carry out such huge tasks manually may delay in time and needs for more clerical works. The major issue in the implementation of such Online Research Management System is because of non – adaptation (which takes care of all the issues mentioned in legacy systems) and incorporating the latest technology in the existing system. The existing system is based on manual evaluation process. Such a manual process consists of collection of data and integration of various data in the form of black and white copies. Findings: To overcome these issues, the proposed system, implementation of the Online Research Management System will be helpful to overcome the above-mentioned drawbacks. The aim of the Online Research Management Systems is to make the process faster and paperless frameworks process. Applications/Improvements: In this regard, the implementation will be helpful in carrying out the following important tasks such as funding scheme, proposal creation, proposal administration, financial management, reports generation and tracking system. Such an automated system will be benefited to the end user side and administration side in timely base.

Object-based 3D geomodel with multiple constraints for early Pliocene fan delta in the south of Lake Albert Basin, Uganda

The early Pliocene fan delta complex developed in the south of Lake Albert Basin which is located at the northern end of the western branch in the East African Rift System. The stratigraphy of this succession is composed of distributary channels, overbank, mouthbar and lacustrine shales. Limited by the poor seismic quality and few wells, it is full of challenge to delineate the distribution area and patterns of reservoir sands. Sedimentary forward simulation and basin analogue were applied to analyze the spatial distribution of facies configuration and then a conceptual sedimentary model was constructed by combining with core, heavy mineral and palynology evidences.A 3D geological model of a 120 m thick stratigraphic succession was built using well logs and seismic surfaces based on the established sedimentary model. The facies modeling followed a hierarchical object-based approach conditioned to multiple trend constraints like channel intensity, channel azimuth and channel width. Lacustrine shales were modeled as background facies and then in turn eroded by distribute channels, overbank and mouthbar respectively. At the same time a body facies parameter was created to indicate the connectivity of the reservoir sands. The resultant 3D facies distributions showed that the distributary channels flowed from east bounding fault to west flank and overbank was adhered to the fringe of channels while mouthbar located at the end of channels. Furthermore, porosity and permeability were modeled using sequential Gaussian simulation (SGS) honoring core observations and petrophysical interpretation results.Despite the poor seismic is not supported to give enough information for fan delta sand distribution, creating a truly representative 3D geomodel is still able to be achieved. This paper highlights the integration of various data and comprehensive steps of building a consistent representative 3D geocellular fan delta model used for numeral simulation studies and field development plan.

Service robot system with an informationally structured environment

Daily life assistance is one of the most important applications for service robots. For comfortable assistance, service robots must recognize the surrounding conditions correctly, including human motion, the position of objects, and obstacles. However, since the everyday environment is complex and unpredictable, it is almost impossible to sense all of the necessary information using only a robot and sensors attached to it. In order to realize a service robot for daily life assistance, we have been developing an informationally structured environment using distributed sensors embedded in the environment. The present paper introduces a service robot system with an informationally structured environment referred to the ROS–TMS. This system enables the integration of various data from distributed sensors, as well as storage of these data in an on-line database and the planning of the service motion of a robot using real-time information about the surroundings. In addition, we discuss experiments such as detection and fetch-and-give tasks using the developed real environment and robot.

창업지원을 위한 공공기관 빅데이터 통합

Nowadays, many small businesses have experienced the failure of business or hardship. In this point, specific and integrated information for startup business should be required to decrease the rate of failure and to increase the rate of success. This study is to suggest the integration of various data which various public institutions have separately. For this purpose, it is to classify the data types in constructing big-data for start-up business and to suggest a way of data integration, analysis method, and web or services of information system for supporting startup businesses.

Utilizing GIS Technology to Improve Fire Prevention Activities in an Urban Fire Department.

The Baltimore City Fire Department (BCFD) has been installing smoke alarms city wide for more than three decades. Though data on each visit are entered into a database, no system existed for using these data for planning or evaluation. The objective of this study is to use Geographic Information System (GIS) technology and existing databases to 1) determine the number of residences in need of a home visit; 2) determine total visits, visits per household, and number of homes entered for eligible households; and 3) demonstrate integration of various data via GIS for use in prevention planning. The tax assessment database was queried to determine the number of eligible (as determined by BCFD policy) residences in need of a visit. Each attempted BCFD home visit was coded to identify, if the BCFD personnel interacted with residents ("pass door") and installed alarms. Home visits were geocoded and compared to the tax assessment database to determine city wide pass door rates. Frequency of visits was run by individual residences to measure efficiency. A total of 206,850 residences met BCFD eligibility for a home visit. In 2007, the BCFD attempted 181,757 home visits and 177,213 were successfully geocoded to 122,118 addresses. A total of 122,118 eligible residences (59%) received a home visit. A total of 35,317 residences (29%) received a repeat visit attempt. The pass door rate was 22% (46,429) of all residences. GIS technology offers a promising means for fire departments to plan and evaluate the fire prevention services they provide.

Integrated Data as backbone of e-Navigation

e-Navigation, a theme introduced by International Maritime Organization (IMO) to improve safety of navigation at sea, is starting to gain traction in various organizations. As the concept develops, the importance of data, both static as well as dynamic, is more and more realized. International Association of Lighthouse Authorities (IALA) and International Hydrographic Organization (IHO), in their efforts to help making e-Navigation a reality, have agreed to propose the IHO GI Register (often known as S-100 Register) as the conceptual basis for the Common Maritime Data Structure (CMDS). Utilizing this common understanding of key players in e-Navigation arena, the IMO e-Navigation Correspondence Group has firmed up the overarching architecture, enabling a series to test beds proving the concept of integration of various data streams to enable improved communication between the stakeholders on shore or at sea. The integration of pre-composed, expert generated navigational data with real time and semi real-time data like Virtual Aids to Navigation (AtoNs), Tide Gages Data or Maritime Safety Information (MSI) transmission from Vessel Traffic Services (VTS) into a single e-Navigation display, if correctly developed, implemented and executed, will be the enabler of increased situational awareness.

Approximate Derivative Computations for the Gradient-Based Optimization Methods in the Local Gradual Deformation for History Matching

Reservoir characterization needs the integration of various data through history matching, especially dynamic information such as production or four-dimensional seismic data. To update geostatistical realizations, the local gradual deformation method can be used. However, history matching is a complex inverse problem, and the computational effort in terms of the number of reservoir simulations required in the optimization procedure increases with the number of matching parameters. History matching large fields with a large number of parameters has been an ongoing challenge in reservoir simulation. This paper presents a new technique to improve history matching with the local gradual deformation method using the gradient-based optimizations. The new approach is based on the approximate derivative calculations using the partial separability of the objective function. The objective function is first split into local components, and only the most influential parameters in each component are used for the derivative computation. A perturbation design is then proposed to simultaneously compute all the derivatives with only a few simulations. This new technique makes history matching using the local gradual deformation method with large numbers of parameters tractable.

Diagenetic controlled reservoir quality of South Pars gas field, an integrated approach

The Dalan-Kangan Permo-Triassic aged carbonates were deposited in the South Pars gas field in the Persian Gulf Basin, offshore Iran. Based on the thin section studies from this field, pore spaces are classified into three groups including depositional, fabric-selective and non-fabric selective. Stable isotope studies confirm the role of diagenesis in reservoir quality development. Integration of various data show that different diagenetic processes developed in two reservoir zones in the Kangan and Dalan formations. While dolomitisation enhanced reservoir properties in the upper K2 and lower K4 units, lower part of K2 and upper part of K4 have experienced more dissolution. Integration of RQI, porosity-permeability values and pore-throat sizes resulted from mercury intrusion tests shows detailed petrophysical behavior in reservoir zones. Though both upper K2 and lower K4 are dolomitised, in upper K2 unit non-fabric selective pores are dominant and fabric destructive dolomitisation is the main cause of high reservoir quality. In comparison, lower K4 has more fabric-selective pores that have been connected by fabric retentive to selective dolomitisation.

History Matching Geostatistical Model Realizations Using a Geometrical Domain Based Parameterization Technique

Reservoir characterization needs the integration of various data through history matching, especially dynamic information such as production or 4D seismic data. Although reservoir heterogeneities are commonly generated using geostatistical models, random realizations cannot generally match observed dynamic data. To constrain model realizations to reproduce measured dynamic data, an optimization procedure may be applied in an attempt to minimize an objective function, which quantifies the mismatch between real and simulated data. Such assisted history matching methods require a parameterization of the geostatistical model to allow the updating of an initial model realization. However, there are only a few parameterization methods available to update geostatistical models in a way consistent with the underlying geostatistical properties. This paper presents a local domain parameterization technique that updates geostatistical realizations using assisted history matching. This technique allows us to locally change model realizations through the variation of geometrical domains whose geometry and size can be easily controlled and parameterized. This approach provides a new way to parameterize geostatistical realizations in order to improve history matching efficiency.

Geographic information system based roadway construction planning

The planning process for roadway construction involves a large amount of information on design, construction methods, quantities, unit costs, production rates, and site conditions. Therefore, it is very important to acquire, manage, and process the necessary information efficiently to produce a rigorous construction plan. The geographic information system (GIS) is a very effective tool for integrating and managing various types of information, including spatial and nonspatial data, required for roadway construction planning. This paper proposes a GIS-based system for improving roadway construction planning with its "interactive space scheduling" and "operation level planning" functions, which are supported by the integration of various data required for planning. The proposed system can assist construction planners in a unique way by integrating design and construction information and creating modularized design elements for space scheduling in real time using its interactive space scheduling function. In addition, operation level planning on earthwork can be conducted via the ability of the system to analyze haul routes in three dimensions and selecting the best equipment combination. It is expected that the proposed system could improve the efficiency of roadway construction planning.Key words: geographic information system (GIS), roadway construction planning, information integration, space scheduling.